AI & Data Analytics Engineer

Overview

We are seeking a highly motivated

AI & Data Analytics Engineer

to join our Internal Audit department. This role will play a critical part in modernizing and streamlining our testing processes through automation,

artificial intelligence (AI)

, advanced analytics, and innovative coding solutions. The Analyst will collaborate with auditors and stakeholders to design, develop, and implement automated and AI-driven testing frameworks that enhance efficiency, accuracy, and insight in our audit practices.

Key Responsibilities

Automation & AI Development :

Design, build, and maintain automated and AI-enhanced testing solutions to support audit activities, streamline manual processes, and increase data-driven insights.

Coding, Scripting & AI Integration :

Develop, document, and maintain scripts and tools (e.g., Python, SQL, R, or similar languages), incorporating machine learning and natural language processing (NLP) models for anomaly detection, predictive analytics, and intelligent audit sampling.

Data Transformation, Analytics & AI Modeling :

Extract, transform, and analyze large datasets using advanced analytics and AI techniques to identify anomalies, trends, and potential risk indicators.

Testing Optimization :

Partner with internal auditors to understand testing objectives and translate them into automated and intelligent approaches that improve efficiency, accuracy, and reliability.

Tool & Process Innovation :

Research and recommend emerging technologies, including AI, generative AI, and machine learning frameworks, that can be applied to audit testing and continuous monitoring.

Collaboration :

Work closely with Internal Audit team members and cross-functional stakeholders to ensure AI-enhanced solutions meet business requirements and align with audit objectives.

Documentation & Training

: Prepare clear documentation of automated and AI-driven testing processes and provide training / support to the audit team on the use of automation and AI tools.

Qualifications :

Experience and Skills :

Bachelor’s Degree in data Analytics, Computer Science, Information Systems, Accounting Information Systems, or a related field.

10 Years+ hands-on coding experience with languages such as Python, R, SQL, or similar.

Familiarity with AI frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and experience integrating

machine learning models

into business workflows.

Understanding of

AI ethics

, model validation, and bias detection.

Experience with data manipulation, automation frameworks, and analytics tools.

Strong understanding of data integrity, data quality, and transformation processes.

Excellent analytical, problem-solving, and critical-thinking skills.

Strong written and verbal communication skills to explain technical concepts to non-technical stakeholders.

Desirable Skills :

Experience in internal audit, risk management, or compliance functions.

Experience using

generative AI tools

(e.g., ChatGPT, GitHub Copilot) for process documentation, analysis, and code generation.

Familiarity with audit testing methodologies or audit management software.

Familiarity with audit testing methodologies or

AI-assisted audit analytics

Experience with data visualization tools (Power BI, Tableau, Qlik, etc.).

Exposure to ETL tools, APIs, or cloud-based data platforms.

Knowledge of

process mining

, continuous auditing, and AI-based risk detection.

Soft Skills :

Effective collaboration and communication skills, with a proven ability to work with interdisciplinary teams.

Strategic thinker with a proactive approach to fraud risk assessment and process optimization.

Commitment to upholding data integrity, confidentiality, and ethical standards in all forensic and data-driven activities.

Travel :

Between 25%-50% travel is required

Amphenol Corporation is an equal opportunity employer and we encourage applications from all qualified candidates.